The Event Horizon for Local Discovery Apps
First, some physics:
You are the little blue man, bottom left, and the blue line is your event horizon, a hard limit defined by the speed of light.
The event horizon is the edge of your cone of influence. Any event can, theoretically, affect any other event occurring within its cone-of-influence.
But you cannot affect any event occurring outside your cone of influence. This set includes:
All events in your past
Simultaneous events, non-zero distance away
Events that are sooner than time t in the future, but further than c*t away. [c is the speed of light, so c*t is a distance]
Every event within your cone of influence is one you can, theoretically, influence — you can be there when it happens!
This is the hard limit of causality, defined by physics, and is effectively theoretical as we can’t yet travel at the speed of light (though, it should be noted, our messages can).
However, if we apply the same math to speeds we can, and do travel, and then apply windows of time that are reasonable to us, we learn something about our physical influence/experience;
Unless our need is urgent, the relevant distance is actually quite large — we don’t care about ‘local’.
This has major implications for local discovery applications.
By way of explanation, let’s tabulate a few speeds at which we frequently move, roughly.
And now let’s tabulate a few things we might want to experience (read co-exist with) and how soon we might need that, roughly. Feel free to make up some of your own.
Now, let’s multiply these two tables together to get a table of distances. Think of the result as a table defining the radius of our ‘cone-of-causality’ for each mode of transport, combined with each need state.
Or put another way, given need for thing T in a certain window of time, and our ability to travel at speed S, how much of the immediate surrounding space is eligible to provide the source of satisfaction for need T.
We see from the result that in all but a few cases, our relevant distance (Table 3 is a table of distances, in km) is on the order of a major metropolitan area, if not much much larger.
Let me pull an example out of this table, to help explain. If I decide I need a dentist within the next 10 hours, and I have a car, that dentist could theoretically be up to 1000 kilometers away, and still satisfy my need.
To be clear, I’m not saying anyone wants to drive 1000 km to their dentist, but if I am in the business of suggesting dentists to prospective clients, I do not need to know their immediate location. I probably just need to know where they live - that’s different information.
I think this point highlights a key insight which has long escaped many entrepreneurs in the ‘local discovery’ space. Many a start up has dashed itself (and its investors’ money) on this non-instinctive result.
It’s not about the ‘location’ in ‘GPS location’. It’s way more relevant to know where we live, and the metropolitan areas in which we spend most of our time.
This applies to all the ‘location-based experience’ offerings. Are you sure your user’s immediate location matters that much? Is their cone-of-immediate influence an appropriate filter for whatever it is you’re offering them?
We are so enchanted at the prospect of enabling users to pluck baubles from their surroundings, as the need occurs to them. Perhaps we fall into this trap because our senses are so dominated by what we see around us, or perhaps because spontaneous need-satisfaction was the dominant paradigm for much of our evolution.
Whatever the cause, it is not a pressing problem except for in the most urgent cases, and as far as needs are concerned, immediate vicinity is inextricably related to urgency.
If it’s not something your user needs right now, their immediate location is not a high-fidelity signal, and you should discount it accordingly.